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Joint congestion control and resource allocation for energy-efficient transmission in 5G heterogeneous networks

机译:共同拥塞控制与5G异构网络节能传输的资源分配

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摘要

Abstract The deployment of small cells with carrier aggregation (CA) is a significant feature of fifth generation (5G) mobile communication systems which could be characterized by the multi-dimensional heterogeneity on their diversified requirements upon different resources. Taking the heterogeneity into account, we consider here a joint optimization problem wherein multiple kinds of resources are concurrently allocated to optimize the system throughput utility while enhancing the network energy efficiency (EE) and maintaining the system stability. Especially, for the high-dimensional non-deterministic polynomial (NP)-hard allocation problem embedded, we conduct a mathematical programming model involving nonlinear integer constraints to seek the long-term stable utility on throughput and introduce an iterative optimal modulation and coding scheme-based (optimal MCS-based) heuristic algorithm as an effective solver. In addition, as data traffic and channel condition will be time-varying in the real world, an admission control based on the Lyapunov technique that requires no prior knowledge on channel information is proposed to reduce the system overhead. Finally, not only the performance bound is derived in theory, but also the numerical experiments are conduced to reveal its characteristics with respect to the system parameter V and the EE requirement.
机译:摘要利用载波聚合(CA)的小单元的部署是第五代(5G)移动通信系统的重要特征,其能够以不同的资源对其多元化要求的多维异质性为特征。考虑到异质性,我们考虑这里考虑一个联合优化问题,其中同时分配多种资源以优化系统吞吐量的实用性,同时增强网络能效(EE)并保持系统稳定性。特别是,对于嵌入的高维非确定性多项式(NP) - 静态分配问题,我们进行了一个涉及非线性整数约束的数学编程模型,以寻求吞吐量的长期稳定实用性,并引入迭代最佳调制和编码方案 - 基于(最优MCS的)启发式算法作为有效的求解器。此外,随着数据流量和频道条件在现实世界中的时变,提出了一种基于Lyapunov技术的准入控制,该方法不需要先前了解信道信息的知识,以减少系统开销。最后,不仅在理论上导出了性能,而且还涉及数值实验,以揭示其关于系统参数V和EE要求的特性。

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